Rewards Analytics and Distribution Dashboard

This goal of this notebook is to offer an easy way to process the outputs of the praise and sourcecred reward systems, perform an analysis of the results and calculate the token reward distribution. It uses mock data and should be considered a work-in-progress.

Imports

First, we import the relevant libraries, get the Data and set how many tokens we want to distribute

Now that we have selected the files, we can import them for processing. We can also set the total amount of tokens we want to distribute this period. We also set the name we want our output file to have.

Tip: Now that the file paths are set, you can safely click on "Cell > Run all below" from here on the menu bar to execute everything :)

Parameters

Set the total amount of tokens we want to distribute this period. We also set the name we want our output file to have.

Results Analysis

Let's dive into some data analysis! We'll use the metrics designed and explained by octopus🐙, and focus only on the praise rewards for now. Starting with:

Allocation percentages - Praise receivers

This table will show us which percentage of the total rewards gets distributed to which top % of users. So "Top 50% -> 0.85" would mean that the top 50% of praisees received 85% of the total rewards

	Rewards
Top 50%	0.944352
Top 20%	0.712005
Top 10%	0.497617
Top 5%	0.322359
Top 1%	0.092784

Allocation Percentages - Praise givers

This table will show us which percentage of the total rewards get distributed based on praise given by which top % of users. So "Top 50% -> 0.85" would mean that 85% of the total rewards are based on praise given by the top 50% praise givers.

	Rewards
Top 50%	0.963308
Top 20%	0.826072
Top 10%	0.654473
Top 5%	0.544064
Top 1%	0.325019

Plotting praise given against praise received

Now we can compare the relationship between praise given by a user and the praise they received

Gini coefficient

Next we will look at the Gini coefficient. Note that there is some debate if we want to use this metric at all, since it is usually employed to measure wealth distribution, and not compensation.

	Rewards
All	0.676756
Top 50%	0.457938
Top 20%	0.273441

Shannon Entropy

Shannon Entropy) is a concept from communications theory, which is also used in measuring the diversity of a distribution. The formula for calculating Shannon Entropy among $n$ individuals is $$\\sum_{k=1}^n -p_k log_2(p_k),$$ where $p_k$ represents the proportion of the resource that user $k$ received.

Here we compare the actual Shannon Entropy with the maximum possible for the dataset, keeping in mind that a Shannon Entropy of 0 would mean one user holds all the rewards

	Rewards
Entropy	5.055404
Max Entropy	6.266787
% of Max	0.806698

Nakamoto Coefficient

Last but not least, the Nakamoto coefficient. The Nakamato Coefficient is defined as the smallest number of accounts who control at least 50% of the resource. Although its significance relates to the prospect of a 51% attack on a network, which may not be relevant in our context, we can still use it as an intuitive measure of how many individuals received the majority of a resource.

9

Praise Data Visualization

Rating distribution

Since praise gets valued on a scale, we can take a look at how often each value of the scale gets assigned by quantifiers.

Praise Reward Distribution

We can also take a look at the distribution of the received praise rewards

Praise Outliers

To aid the revision process, we can generate a table which sorts the praise by the size of the spread between the highest and lowest scores. These "controversial" praise instances can then be discussed in the quantifier review call. Index numbers are kept to make localization in the "big praise sheet" easier.

	index	ID	DATE	TO USER ACCOUNT	FROM USER ACCOUNT	REASON	SCORE 1	SCORE 2	SCORE 3	DUPLICATE ID 1	DUPLICATE ID 2	DUPLICATE ID 3	DISMISSED 1	DISMISSED 2	DISMISSED 3	QUANTIFIER 1 USERNAME	QUANTIFIER 2 USERNAME	QUANTIFIER 3 USERNAME	AVG SCORE	SPREAD
0	405	621f79e143b89009366c8677	2021-07-28T22:00:00.000Z	karmaticacid#1218	Vyvy-vi#5040	for recording the GIVeconomy talk, and saving ...	144	0	55	None	None	None	False	True	False	Usua◎ Silver#2618	liviade#1387	shawn#7046	99	144
1	326	621f79e143b89009366c85c2	2021-07-18T22:00:00.000Z	liviade#1387	griff (💜, 💜)#8888	for being brave enough to let it happen	144	5	1	None	None	None	False	False	False	Usua◎ Silver#2618	tigeroid#2951	divine_comedian#5493	50	143
2	506	621f79e143b89009366c86ee	2021-07-30T22:00:00.000Z	natesuits#4789	iviangita#3204	for parameters content in the forum	144	8	1	None	None	621f79e143b89009366c86d1	False	False	False	Usua◎ Silver#2618	tigeroid#2951	shawn#7046	52	143
3	547	621f79e143b89009366c8717	2021-07-30T22:00:00.000Z	griff (💜, 💜)#8888	Mount Manu#3530	for their work building the Commons Configurat...	2	144	34	621f79e143b89009366c868a	None	None	False	False	False	AmwFund#0979	bends#3537	shawn#7046	60	142
4	10	621f79e143b89009366c846e	2021-07-12T22:00:00.000Z	JeffEmmett#7202	griff (💜, 💜)#8888	for hacking on the buckets for Praisemaggeden ...	144	3	21	None	None	None	False	False	False	Usua◎ Silver#2618	bends#3537	calazki#3961	56	141
5	521	621f79e143b89009366c86fd	2021-07-30T22:00:00.000Z	sem 🐝#0161	Mount Manu#3530	for all the dancing	144	5	3	None	None	None	False	False	False	Usua◎ Silver#2618	bends#3537	shawn#7046	50	141
6	410	621f79e143b89009366c867c	2021-07-28T22:00:00.000Z	Alp#3768	Mount Manu#3530	for a 2-hour onboarding session full of questi...	144	8	3	None	None	None	False	False	False	Usua◎ Silver#2618	bends#3537	Mettodo#7010	51	141
7	24	621f79e143b89009366c847c	2021-07-12T22:00:00.000Z	liviade#1387	griff (💜, 💜)#8888	for jumping in and observing the Praise Audit ...	144	3	13	None	None	None	False	False	False	Usua◎ Silver#2618	tigeroid#2951	divine_comedian#5493	53	141
8	0	621f79e143b89009366c841c	2021-07-11T22:00:00.000Z	Suga#8514	Vyvy-vi#5040	for making edits in the welcome text	3	3	144	None	None	None	False	False	False	Tam2140#9361	Vyvy-vi#5040	Mettodo#7010	50	141
9	145	621f79e143b89009366c8502	2021-07-15T22:00:00.000Z	acidlazzer#5796	iviangita#3204	for all of their contributions to comms	144	3	5	None	None	621f79e143b89009366c841e	False	False	False	Usua◎ Silver#2618	liviade#1387	calazki#3961	49	141
10	593	621f79e143b89009366c8745	2021-07-30T22:00:00.000Z	Alp#3768	Mount Manu#3530	for devoting 20 minutes to going through our C...	144	3	3	None	None	None	False	False	False	Usua◎ Silver#2618	bends#3537	Mettodo#7010	50	141
11	496	621f79e143b89009366c86e4	2021-07-30T22:00:00.000Z	acidlazzer#5796	iviangita#3204	for helping with Gravity’s infographics	144	14	5	None	621f79e143b89009366c867b	621f79e143b89009366c841e	False	False	False	Usua◎ Silver#2618	liviade#1387	calazki#3961	48	139
12	376	621f79e143b89009366c8606	2021-07-25T22:00:00.000Z	karmaticacid#1218	griff (💜, 💜)#8888	for helping me write and rewrite the forum pos...	144	5	55	None	None	None	False	False	False	Usua◎ Silver#2618	liviade#1387	shawn#7046	68	139
13	168	621f79e143b89009366c8519	2021-07-15T22:00:00.000Z	liviade#1387	iviangita#3204	for the Impact Hour spreadsheet	144	5	14	None	None	621f79e143b89009366c8514	False	False	False	Usua◎ Silver#2618	tigeroid#2951	divine_comedian#5493	51	139
14	548	621f79e143b89009366c8718	2021-07-30T22:00:00.000Z	markop#2007	Mount Manu#3530	for their work building the Commons Configurat...	144	5	5	None	621f79e143b89009366c865e	621f79e143b89009366c865e	False	False	False	Usua◎ Silver#2618	liviade#1387	calazki#3961	49	139
15	191	621f79e143b89009366c8530	2021-07-15T22:00:00.000Z	Nuggan#5183	iviangita#3204	for jumping in params, giving feedback and ask...	144	5	89	None	None	None	False	False	False	Usua◎ Silver#2618	liviade#1387	shawn#7046	79	139
16	526	621f79e143b89009366c8702	2021-07-30T22:00:00.000Z	OddName#8763	iviangita#3204	for the amazing brainstorming around governanc...	144	13	5	None	None	None	False	False	False	Usua◎ Silver#2618	Vyvy-vi#5040	Mettodo#7010	54	139
17	409	621f79e143b89009366c867b	2021-07-28T22:00:00.000Z	acidlazzer#5796	Juankbell#7458	for helping with Gravity's infographics! this ...	144	5	14	None	None	621f79e143b89009366c865c	False	False	False	Usua◎ Silver#2618	liviade#1387	calazki#3961	50	139
18	384	621f79e143b89009366c865c	2021-07-25T22:00:00.000Z	acidlazzer#5796	David (please DYOR...)#4116	for relentlessly pumping out the graphics💛	144	5	21	None	None	None	False	False	False	Usua◎ Silver#2618	liviade#1387	calazki#3961	56	139
19	128	621f79e143b89009366c84f1	2021-07-15T22:00:00.000Z	Nuggan#5183	iviangita#3204	for making the params parties work out	144	5	14	None	None	621f79e143b89009366c8530	False	False	False	Usua◎ Silver#2618	liviade#1387	shawn#7046	52	139
20	288	621f79e143b89009366c859b	2021-07-15T22:00:00.000Z	sem 🐝#0161	iviangita#3204	for engaging in discussion on the TE Commons F...	144	5	55	None	None	None	False	False	False	Usua◎ Silver#2618	bends#3537	shawn#7046	68	139
21	425	621f79e143b89009366c868b	2021-07-28T22:00:00.000Z	markop#2007	divine_comedian#5493	for their work building to the commons config ...	144	8	5	None	None	621f79e143b89009366c865e	False	False	False	Usua◎ Silver#2618	liviade#1387	calazki#3961	52	139
22	264	621f79e143b89009366c8579	2021-07-15T22:00:00.000Z	iviangita#3204	Mount Manu#3530	for stewarding this community successfully int...	5	144	8	None	None	None	False	False	False	Tam2140#9361	bends#3537	divine_comedian#5493	52	139
23	594	621f79e143b89009366c8746	2021-07-30T22:00:00.000Z	Alp#3768	Mount Manu#3530	for diving deep into the TEC, devoting several...	144	34	8	None	None	None	False	False	False	Usua◎ Silver#2618	bends#3537	Mettodo#7010	62	136
24	220	621f79e143b89009366c854d	2021-07-15T22:00:00.000Z	liviade#1387	Mount Manu#3530	for helping Zer8 around	144	8	8	None	None	None	False	False	False	Usua◎ Silver#2618	tigeroid#2951	divine_comedian#5493	53	136

We can also plot the spread against the average score for a more visual search.
ATTENTION! Keep in mind that this is just meant as a visual aid. If there are several praise instances with similar spread and average quant number, all but one end up "hidden" on the chart. For the full list you have to use the table.

Praise Flows

Now for something more fun: let's surface the top "praise flows" from the data. Thanks to @inventandchill for this awesome visualization! On one side we have the top 20 praise givers separately (modifiable by changing the variable n_senders), on the other the top 25 receivers (modifiable by changing the variable n_receivers). The people outside the selection get aggregated into the "REST FROM" and "REST TO" categories.

SourceCred Data

SourceCred token Distribution

Next we can see the distribution made by the SourceCred algorithm.

Quantifier Data

Let's take a closer look at each quantifier. In the following step we will use the raw praise data to zoom in on how each quantifier scored the praises:

Amount of praise quantified

With the above table we can easily see how much praise each quantifier rated.

Mean praise score by quantifier

Let's see the mean praise scores every quantifier gave.

Total Token Distribution Visualization and Export

To send the allocations to the DAO for distribution, we need to put all data together and add the rewards for the reward board and the quantifiers.

Let's take a final look at the total distribution. Click on the legend to filter out specific reward sources

That's it! We can now download the final distribution files and upload them to GitHub for future reference. We want to export 3 different files:
 - The final reward allocations, separated by source
 - The final reward allocations, in a disperse.app-readable format
 - The extended praise data, detailing the how many tokens each single praise netted (for future reference)